基于电成像测井的火山碎屑砂砾岩支撑类型评价  

Evaluation of Support Types of Volcanic Clastic Sand and Gravels Based on Electrical Imaging Logging

作　　者：赵小青[1,2] 王翔宇 张志国 张维峰 陈海峰 ZHAO Xiaoqing;WANG Xiangyu;ZHANG Zhiguo;ZHANG Weifeng;CHEN Haifeng(Accumulation and Development of Continental Oil and Gas Key Laboratory of Education Ministry,Northeast Petroleum University,Daqing,Heilongjiang 163318,China;School of Earth Sciences,Northeast Petroleum University,Daqing,Heilongjiang 163318,China;Daqing Branch,China National Logging Corporation,Daqing,Heilongjiang 163318,China;Key Laboratory of Oil and Gas Reservoir Formation Mechanism and Resource Evaluation in Heilongjiang Province,Northeast Petroleum University,Daqing,Heilongjiang 163318,China)

机构地区：[1]东北石油大学陆相页岩油气成藏及高效开发教育部重点实验室,黑龙江大庆163318 [2]东北石油大学地球科学学院,黑龙江大庆163318 [3]中国石油集团测井有限公司大庆分公司,黑龙江大庆163318 [4]东北石油大学油气藏形成机理与资源评价黑龙江省重点实验室,黑龙江大庆163318

出　　处：《测井技术》2023年第3期326-333,共8页Well Logging Technology

摘　　要：火山碎屑砂砾岩在沉积过程中受河流搬运与火山作用共同影响,造成岩石粒径变化大、不同粒级组合的孔隙结构复杂,影响储层品质。如何利用测井资料评价岩石粒级及不同粒级的组合模式是储层评价亟待解决的问题。依据X衍射的全岩分析实验结果得出研究区主要矿物成分及母岩类型特征。通过观察岩心照片结合岩电实验数据,发现研究区火山碎屑砂砾岩普遍存在骨架含有酸性火山岩的低阻砾石及正常沉积的高阻砾石。基于微电阻率扫描成像测井资料,利用分水岭算法,定量计算高、低阻砾石含量,并建立研究区岩性识别划分标准。在基于滑动窗口法生成的粒度谱基础上,构建粒度面积谱用来定量评价不同粒级砾石的含量,以获得不同粒级砾石的分布特征。通过分析岩心不同粒级组合关系的含油性特征,确定砾石颗粒支撑类型,结合粒度谱及粒度面积谱,形成基于电成像测井的火山碎屑砂砾岩支撑类型评价方法。该方法充分利用电成像测井资料在砾石识别中的优势,为火山碎屑砂砾岩岩性识别及粒级组合模式评价提供了重要手段。The combined effect of river transport and volcanic action during the deposition of volcanic clastic sand conglomerate causes large variations in rock grain size and complex pore structure of different grain size combinations,which affects the reservoir quality.How to use logging date to evaluate rock grain size and the combination patterns of different grain sizes is an urgent problem to be solved in resevoir evaluation.The main mineral composition and parent rock type characteristics of the study area were obtained based on the whole-rock analysis experimental results of X diffraction.By observing core photos combined with petrographic experimental data,it is found that the volcanic clastic sand conglomerates in the study area commonly have a skeleton containing low-resistance conglomerates of acidic volcanic rocks and high-resistance conglomerates of normal deposition.Based on the micro-resistivity scanning imaging logging data,the watershed transformation algorithm was used to quantitatively calculate the content of high and low resistance gravels and to establish the lithological identification classification criteria in the study area.Based on the particle size spectrum generated by the sliding window method,an particle size area spectrum was constructed to quantitatively evaluate the content of different gravel grades to obtain the distribution characteristics of different gravel grades.By analyzing the oil-bearing characteristics of the core in relation to different grain-size combinations,the support type of gravel particles is determined,and the combination of the particle size spectrum and the particle size area spectrum results in an evaluation method of the support type of volcanic clastic sand conglomerate based on electrical imaging logging.The method makes full use of the advantages of electrical imaging logging data in gravel identification,and provides an important means to finely delineate the lithology identification and grain-size combination pattern evaluation of volcanic clastic sand conglo

关 键 词：测井评价 火山碎屑砂砾岩 母岩类型 微电阻率扫描成像测井 粒度面积谱 砾石颗粒支撑类型 海拉尔盆地乌尔逊凹陷 

分 类 号：P631.84[天文地球—地质矿产勘探]